New approximations of differential entropy for independent component analysis and projection pursuit
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A Unified Model for Probabilistic Principal Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Probabilistic Principal Surfaces for Yeast Gene Microarray Data Mining
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Clustering and visualization approaches for human cell cycle gene expression data analysis
International Journal of Approximate Reasoning
PCA Based Feature Selection Applied to the Analysis of the International Variation in Diet
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Using the Negentropy Increment to Determine the Number of Clusters
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Normality-based validation for crisp clustering
Pattern Recognition
NEC for gene expression analysis
WILF'05 Proceedings of the 6th international conference on Fuzzy Logic and Applications
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In this paper a hierarchical agglomerative clustering is introduced. A hierarchy of two unsupervised clustering algorithms is considered. The first algorithm is based on a competitive Neural Network or on a Probabilistic Principal Surfaces approach and the second one on an agglomerative clustering based on both Fisher and Negentropy information. Different definitions of Negentropy information are used and some tests on complex synthetic data are presented.